Data driven discovery in catalysis involves the use of computational tools and algorithms to analyze large datasets generated from experimental and theoretical studies. This approach helps in identifying patterns, predicting outcomes, and uncovering new insights that may not be apparent through conventional methods. By utilizing big data and statistical models, researchers can make informed decisions faster and more accurately.
